This tutorial will get you started with Pandas - a data analysis library for Python that is great for data preparation, joining, and ultimately generating well-formed, tabular data that's easy to use in a variety of visualization tools or (as we will see here) machine learning applications.

Got an idea for a great Kaggle competition? Let us know! When I came to Kaggle for my first day of work, David, one of our awesome data scientists, greeted me at the door wearing a shirt of me: There is a reasonable explanation of why David was wearing a shirt of me. At Kaggle, many of our best hires have come in through the Kaggle community and our personal networks (like the Google Predict meetup where I met David.) ...

About two months ago I joined Kaggle as product manager, and was immediately given a hard time by just about everyone because I hadn't ever made a real submission to a Kaggle competition. I had submitted benchmarks, sure, but I hadn't really competed. Suddenly, I had the chance to not only geek out on cool data science stuff, but to do it alongside the awesome machine learning and data experts in our company and community. But where to start? I ...